以中国传统腌腊肉为对象,研究用近红外光谱分析技术快速准确检测肉制品品质的可行性。腊肉是富含脂肪的肉制品,其酸价是目前国标中必须检测的品质指标,它可以反映腊肉在加工储藏过程中脂肪氧化酸败的情况,对腊肉的品质尤为重要。腊肉样品经过简单的粉碎后在BRUKER傅里叶变换近红外光谱仪上扫描,获得其近红外光谱参照国标法测定酸价和水分含量,采用附加散射校正光谱预处理方法,建立了腊肉酸价和水分含量的PLS回归模型。酸价模型预测集中样品的预测值与标准值的相关系数r^2为0.98,预测标准差RMSECV为0.25;水分含量模型预测集中样品的预测值与标准值的r^2为0.90,RMSECV为0.02。成对t检验统计结果表明近红外光谱分析技术可以用于腊肉制品品质的快速检测。
The feasibility of fast and correctly detecting the quality of Chinese bacon by NIR was studied. The acid value (AV) can reflect the quality of Chinese bacon during processing and storage which is prescribed in the Chinese national standard methods definitely. The fat is abundant in Chinese bacon, so the AV index is important for the quality of Bacon. Samples were scanned on the Bruker FTNIR reflected spectra instrument after being ground. The preprocess method of Additional Scattered Correction was used for the mathematic model of AV and moisture content of Chinese Bacon by PLS. The correlation ratio and the RMSCV of AV and moisture content of the prediction set were 0, 98, 0. 25, 0. 90 and 0.02 respectively, The results showed that NIR spectroscopy analysis technology can be used for fast detecting AV and moisture content of Chinese Bacon.